000 03673nam a22004935i 4500
001 978-3-540-34956-3
003 DE-He213
005 20170628034522.0
007 cr nn 008mamaa
008 100301s2006 gw | s |||| 0|eng d
020 _a9783540349563
_9978-3-540-34956-3
024 7 _a10.1007/978-3-540-34956-3
_2doi
050 4 _aTA329-348
050 4 _aTA640-643
072 7 _aTBJ
_2bicssc
072 7 _aMAT003000
_2bisacsh
082 0 4 _a519
_223
100 1 _aAbraham, Ajith.
_eeditor.
245 1 0 _aSwarm Intelligence in Data Mining
_h[electronic resource] /
_cedited by Ajith Abraham, Crina Grosan, Vitorino Ramos.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg,
_c2006.
300 _aXVIII, 268 p. 91 illus., 5 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aStudies in Computational Intelligence,
_x1860-949X ;
_v34
505 0 _aSwarm Intelligence in Data Mining -- Ants Constructing Rule-Based Classifiers -- Performing Feature Selection with ACO -- Simultaneous Ant Colony Optimization Algorithms for Learning Linguistic Fuzzy Rules -- Ant Colony Clustering and Feature Extraction for Anomaly Intrusion Detection -- Particle Swarm Optimization for Pattern Recognition and Image Processing -- Data and Text Mining with Hierarchical Clustering Ants -- Swarm Clustering Based on Flowers Pollination by Artificial Bees -- Computer study of the evolution of ‘news foragers' on the Internet -- Data Swarm Clustering -- Clustering Ensemble Using ANT and ART.
520 _aSwarm Intelligence is an innovative distributed intelligent paradigm for solving optimization problems that originally took its inspiration from the biological examples by swarming, flocking and herding phenomena in vertebrates. Data Mining is an analytic process designed to explore large amounts of data in search of consistent patterns and/or systematic relationships between variables, and then to validate the findings by applying the detected patterns to new subsets of data. This book deals with the application of swarm intelligence in data mining. Addressing the various issues of swarm intelligence and data mining using different intelligent approaches is the novelty of this edited volume. This volume comprises of 11 chapters including an introductory chapter giving the fundamental definitions and some important research challenges. Important features include the detailed overview of the various swarm intelligence and data mining paradigms, excellent coverage of timely, advanced data mining topics, state-of-the-art theoretical research and application developments and chapters authored by pioneers in the field. Academics, scientists as well as engineers engaged in research, development and application of optimization techniques and data mining will find the comprehensive coverage of this book invaluable.
650 0 _aEngineering.
650 0 _aArtificial intelligence.
650 0 _aEngineering mathematics.
650 1 4 _aEngineering.
650 2 4 _aAppl.Mathematics/Computational Methods of Engineering.
650 2 4 _aArtificial Intelligence (incl. Robotics).
700 1 _aGrosan, Crina.
_eeditor.
700 1 _aRamos, Vitorino.
_eeditor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783540349556
830 0 _aStudies in Computational Intelligence,
_x1860-949X ;
_v34
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-540-34956-3
912 _aZDB-2-ENG
999 _c20239
_d20239